Oppo Reno9 Pro+ 5G OPPO PGW110
Geekbench AI Score
1322
Single Precision Score
1315
Half Precision Score
3075
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | rennsport |
| Upload Date | March 13 2025 03:21 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO PGW110 |
| Model ID | OPPO PGW110 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 14.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
616
114.6 IPS |
|
|
Image Classification (HP)
|
100% |
610
113.4 IPS |
|
|
Image Classification (Q)
|
100% |
2204
409.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
777
12.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
743
12.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
2438
39.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2702
3.15 IPS |
|
|
Pose Estimation (HP)
|
100% |
2654
3.10 IPS |
|
|
Pose Estimation (Q)
|
84% |
6050
7.17 IPS |
|
|
Object Detection (SP)
|
100% |
582
46.2 IPS |
|
|
Object Detection (HP)
|
100% |
577
45.8 IPS |
|
|
Object Detection (Q)
|
83% |
2135
172.5 IPS |
|
|
Face Detection (SP)
|
100% |
1927
22.9 IPS |
|
|
Face Detection (HP)
|
100% |
1935
23.0 IPS |
|
|
Face Detection (Q)
|
95% |
4843
57.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2568
19.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
2562
19.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
5105
46.8 IPS |
|
|
Style Transfer (SP)
|
89% |
4422
5.74 IPS |
|
|
Style Transfer (HP)
|
89% |
4465
5.80 IPS |
|
|
Style Transfer (Q)
|
98% |
13078
16.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1399
51.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1410
52.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3409
126.3 IPS |
|
|
Text Classification (SP)
|
100% |
676
902.7 IPS |
|
|
Text Classification (HP)
|
100% |
677
903.0 IPS |
|
|
Text Classification (Q)
|
88% |
1274
1.72 KIPS |
|
|
Machine Translation (SP)
|
100% |
1049
18.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1058
18.2 IPS |
|
|
Machine Translation (Q)
|
50% |
777
27.6 IPS |
